We probably agree that relevant, effectively usable “data” are one key ingredient to approaching the grand challenges of the 21st century. Their central role is demonstrated daily in areas ranging from economics to climate science, from the digital humanities to malaria research. Liveable cities can be built only if we learn from data over longer time frames and, increasingly, these data are collected by citizens. Tackling climate change fundamentally relies on scientists’ ability to analyze reliable time-series data from diverse sources.

It’s a curious pattern, that when new technologies arise and enable access to new forms of data, it is often not the domain experts who drive innovation, but those with deep technical expertise who pick up the required domain knowledge along the way. In other words, it can be a costly mistake to ignore new methods. Let me illustrate this pattern with three examples, before making the connection to "big data."

As an organization scientist, I am interested in how knowledge workers create, use, and maintain their social networks to get their jobs done. I was trained as an ethnographer, and I observe people at work for a living. What, one might ask, does this small-data girl have to say about Big Data?

"Will we live in a beautiful Utopia or a dystopian Big Brother society?" Journalists, politicians, and even random acquaintances ask this question when they learn about my work with Big Data and cities. In fact, most researchers and practitioners working in the Big Data space have shared this experience.